Senior Research Scientist, Agent Evaluation

We build the evaluation layer that validates AI agents before they reach customers - an automated system that scores across large volumes of agent traces.
Youll own core parts of that platform: the pipeline that runs traces through model-based judges at scale, and the scoring logic that turns raw output into results teams can act on.

What youll do

• Design evaluation methodologies and benchmarks for agent reasoning, planning, tool use, reliability, and safety - across LLM-as-a-Judge, trajectory-based, and human evaluation
• Take problems from research question to prototype to shipped feature, owning them end to end
• Build and harden the pipelines and scoring logic behind customer-facing evaluation
• Curate synthetic and real-world datasets; measure the evaluator itself for consistency and agreement with human labels Qualifications

What were looking for

• 5+ years in ML, applied AI, prompt engineering, agentic AI, including shipping something real to users

• Strong Python skills

• Practical depth in agentic AI and context engineering: planning, reasoning, memory, tool use, retrieval, long-context

• Experience designing evaluation methodologies, not just running evaluations

• Hands-on production work with LLM APIs - prompt engineering, structured output, cost and latency tradeoffs

• Clear communication with technical and non-technical audiences

• Good to have Experience with AI-assisted development tools (Claude code, Windsurf, or similar)

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